No limit Texas Hold ‘Em is even more of a challenge because it is a particularly complex form of poker that relies heavily on long-term betting strategies and game theory. In no-limit Hold ‘Em, the goal is to win the most money rather than each hand.

As a result good players use strategies that play out over dozens of hands - sometimes losing on purpose and betting low even though they have good cards.

“It splits its bets into three, four, five different sizes,” one of the competitors, Daniel McAulay, explained to Wired about Libratus’ strategy. “No human has the ability to do that.”

Labratus was designed by Professor Tuomas Sandholm and grad student Noam Brown. During the 20 day competition, the AI comfortably beat its four competitors by raking in more than $1.7 million worth of chips.

Andrew Ng, chief Scientist at Baidu, the Chinese internet company and one of the biggest web corporations in the world, described result as a “stunning accomplishment” which “made history.” He compared it to the iconic 1997 victory of IBM’s Deep Blue over then-reigning chess world champion, Russia’s Gary Kasparov.

The technology has far greater uses than just making professional gamblers feel bad.

The algorithms used by Libratus could also be used to create strategies for applications involving cybersecurity, business transactions, and medicine, which are all areas of research Sandholm and his colleagues work on in Carnegie Mellon.